Demographic Diversity and Employee Attitudes: An ... - CiteSeerX

Journal of Applied Psychology 1997, Vol. 82. No. 3, 342-358

Copyright 1997 by the American Psychological Association, Inc. 0021-9010/97/J3.00

Demographic Diversity and Employee Attitudes: An Empirical Examination of Relational Demography Within Work Units Christine M. Riordan

Lynn McFarlane Shore

University of Georgia

Georgia State University

In this study the authors examined the effects of an individual's similarity to the demographic composition of the workgroup on individual-level attitudes with 98 workgroups from a life insurance company. Results indicated that similarity in race-ethnicity affected individuals' attitudes toward their work group, as well as perceptions of advancement opportunities. Nonsignificant results were found for both similarity in gender and tenure. These findings suggest that demographic variables may have differing complexities in their effects on employee attitudes within work units.

Organizations are facing changes in the demographic composition of the workforce due to labor and market trends, legislation, and demographic realities (Triandis, Kurowski, & Gelfand, 1993). As a result of the changing composition, managers are encountering demographic diversity "much more frequently and at higher levels both inside and outside their organizations" (Triandis et al., 1993, p. 669) than they have in the past. Nonetheless, there is limited empirical research that examines the impact of demographic diversity within work organizations (Jackson, Stone, & Alvarez, 1992). To date, much of the research on demographic diversity has examined the effects of individual characteristics, such as race and sex, on employee attitudes and behaviors (e.g., Graddick & Fair, 1983; Ottaway & Bhatnagar, 1988). Recently, however, some researchers have also indicated that diversity research must consider not only individual demographic variables, but also situational variables that comprise the social context within which the individual operates (e.g., Cleveland & Shore, 1992; Ferris, Judge, Chachere, & Liden, 1991; Kanter, 1977; Wagner, Pffeffer, & O'Reilly, 1984). Individual demographic vari-

ahles, by themselves, may not adequately reflect the full meaning and impact of diversity within a work setting, especially because most individuals work within a social context such as a work unit. Therefore, a complete examination of diversity needs to address individuals within the context of this social environment. One theory that provides a basis for predicting how individual demographic characteristics and the social context interact is relational demography (Mowday & Sutton, 1993). Relational demography: proposes that individuals compare their own demographic characteristics with those of others in their social units to determine if they are similar or dissimilar in their demographic characteristics to the composition of the unit (Tsui, Egan, & O'Reilly, 1992; Tsui & O'Reilly, 1989). The level of an individual's similarity or dissimilarity in demographic attributes to the composition of his or her social unit, in turn, is proposed to affect the individual's work-related attitudes and behaviors. Thus, the same individual demographic characteristic may yield different work-related attitudes in different social contexts. In other words, relational demography proposes that it is the relative, not the absolute, demographic characteristics that are predictive of individuals' workrelated attitudes. For example, Zenger and Lawrence (1989) found that the more similar an individual's age was relative to the ages of the rest of the members of his

Christine M. Riordan, Department of Management, Terry College of Business, University of Georgia; Lynn McFarlane Shore, Department of Management and W. T. Beebe Institute of Personnel and Employment Relations, Georgia State University. An earlier version of this article was presented at the llth Annual Conference of the Society for Industrial and Organizational Psychology (May 1996). We thank Life Office Management Association, Inc., for sponsoring this project. Correspondence concerning this article should be addressed to Christine M. Riordan, Department of Management, Terry College of Business, University of Georgia, Athens, Georgia 30602. Electronic mail may be sent via Internet to criordan® uga.cc.uga.edu.

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It should be noted that the term relational demography has also been used to refer to the demographic similarity between a dyad, such as a supervisor and his/her subordinate (Tsui & O'Reilly, 1989). However, this study is not concerned with the dyadic level of analysis, Rather, this study is concerned with relational demography as it pertains to the individual's demographic similarity relative to an entire group or subgroup of individuals (i.e., relational demography as a cross-level theory). As such, this study concentrates on the literature and previous research that address this level of analysis. 342

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or her project group, the more frequently the individual communicated with the other members concerning technical issues. At present, the research on relational demography is still in an early and developing stage. Whereas previous research on relational demography has been influential, many researchers have suggested that a number of extensions are warranted (e.g., Mowday & Sutton, 1993; Wagner et al., 1984). The overall objective of this study, therefore, is to extend the relational demography research to include a variety of individual-level outcomes that may be affected by the demographic similarity of individuals with their work units, specifically for the three demographic characteristics of gender, race-ethnicity,3 and tenure. Theoretical Background Underlying the concept of relational demography is the construct of demographic similarity that characterizes the degree to which an individual's demographic attributes are shared by other members of a social unit. Historically, the conceptual foundation for research on relational demography within social units (e.g., Tsui et al., 1992) has been social identity theory (Tajfel, 1978), self-categorization theory (Turner, 1982, 1984), and the similarityattraction paradigm (Byrne, 1971). These theories as they pertain to relational demography are briefly discussed below. Both social identity and self-categorization theories propose that an individual's self-definition or self-identity is determined, in part, by his or her group memberships. According to self-categorization theory (Turner, 1987), individuals may use demographic characteristics such as age, race-ethnicity, or gender to classify themselves and others into social categories. In general, "self-categorization theory assumes that people evaluate self-defining categories [such as gender] positively and are motivated to maintain such evaluations. Positive evaluation of self categories is associated with positively evaluating others who fit within the same category" (Jackson et al., 1992, p. 77). In general, then, demographic characteristics may be relevant categories that individuals use as part of their self-identity in the context of a given social unit, such as an organization or a work group (Tsui et al., 1992). The social unit may be more attractive to the individual if it is composed of others whose demographic profiles are consistent with the categories that the individual has chosen to categorize him- or herself (Tsui et al., 1992). For example, if an individual uses gender as a category for self-definition, the individual may be most attracted to and satisfied in groups that are composed of members of the same gender category because the group contains an important part of the individual's existing self-identity

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(Tsui et al., 1992). Conversely, a social unit will be less attractive to the individual if it is inconsistent with the individual's own demographic categories and, thus, selfidentity. Additionally, research has indicated that as the proportion of individuals who possess a particular characteristic (e.g., female) grows smaller, people who possess the minority characteristic will become increasing selfaware of their social identity (Ethier & Deaux, 1994; McGuire, McGuire, Child, & Rijioka, 1978; Mullen, 1983). A situational setting, such as a work group, in which an individual is dissimilar to a majority of the members may make the individual uncomfortable because of the increased awareness that the characteristics of his or her social identity are different from others and, thus, result in lower attitudes and behaviors (Mullen, 1983). The similarity-attraction paradigm yields predictions that are consistent with social identity and self-categorization theories. The similarity-attraction paradigm states that individuals who possess similar individual characteristics and attitudes will perceive one another as similar and will be attracted to each other. That is, both selfcategorization and social identity theories propose that a person's motivation to maintain a positive self-identity is a partial explanation for the effects of the similarityattraction paradigm (Jackson et al., 1992). Although early research on the similarity-attraction paradigm focused primarily on the similarity of attitudes between individuals and their levels of interpersonal attraction, it has also been extended to include a variety of dimensions, such as demographic characteristics, as the basis for similarity in attitudes and thus, interpersonal attraction (Baskett, 1973). For example, Jackson et al. (1991) found that the greater a top management team member's dissimilarity in education level, college curriculum, and industry experience relative to the rest of his or her team, the more likely the individual was to leave the employing organization (i.e., turnover). Research on the similarity-attraction paradigm has found that people are drawn to others who are similar (e.g., Baskett, 1973; Byrne, 1971; Byrne, Clore, & Worchel, 1966; Jackson et al., 1991; Lincoln & Miller, 1979; Werner & Parmelee, 1979). In addition to leading to high levels of interpersonal attraction, research has also shown that similarity between individuals may lead to desired outcomes such as frequent communication, high social integration within a group, and a desire to maintain group affiliation (e.g., Lincoln & Miller, 1979). Settings

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In this study, we classified employees as White, African American, or Hispanic on the basis of self-report responses. Because the category of Hispanic is generally considered an ethnic group and the classifications of White and African American are considered racial groups, we chose the designation of race-ethnicity to reflect the nature of the variable we were studying.

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in which individuals are similar in terms of their demographic characteristics may, thus, offer individuals certain advantages over other settings, "such as the opportunity to interact with similar others and enjoy more cohesive work relations" (Wharton & Baron, 1987, p. 367). Hypotheses Each of the previously discussed theories underlying relational demography suggest that individuals' work-related attitudes and behaviors may be affected by the degree to which the individuals' demographic characteristics are similar to those of others in their social units. Within this study, we examined the three demographic characteristics of gender, race-ethnicity, and tenure as the indicators for demographic similarity (Jackson et al., 1991; Tsui et al., 1992; Wagner et al., 1984; Zenger & Lawrence, 1989). Several reasons justified the selection of these three particular demographic attributes. For one, previous research has indicated that because both gender and raceethnicity are easily detected demographic characteristics, diey are often the basis for the way individuals spontaneously categorize each other (Stangor, Lynch, Duan, & Glass, 1992). Thus, individuals may readily assess whether they are similar to others based on these two demographic characteristics. Second, whereas tenure is not an observable characteristic, it is often thought of as a basis for strong cohort effects (Pfeffer, 1983). Within these tenure cohorts, the similarity among individuals in organizational tenure implies shared language and experiences, as well as a common basis for the ways individuals interpret, respond to, and understand information (Wiersema & Bird, 1993; Zenger & Lawrence, 1989). Overall, research suggests that individuals are likely to associate with others who entered the organization at the same time (or approximately the same time) because they have a similar perspective on the group or the organization and its operations (McCain, O'Reilly, & Pfeffer, 1983). In addition, previous research has specifically identified two sets of outcomes that may be affected by an individual's demographic similarity to the work unit: (a) an individual's attitudes toward the work group itself (Wagner et al., 1984) and (b) an individual's perceptions of advancement opportunities (Wagner et al., 1984). The relationships between each of these outcomes and demographic similarity are discussed below. Demographic Similarity and Work Group Attitudes With the increased organizational reliance on work groups, as evidenced by the appearance of project teams, focus groups, autonomous work groups, quality circles, multifunction work teams, and team chief executive officers, both practitioners and researchers have expressed the

need to better understand work group functioning within organizations (Guzzo & Shea, 1992). An examination of the effects of relational demography provides useful information to increase this understanding. Whereas previous studies on relational demography have examined a variety of organizationally relevant criteria such as organizational commitment (Tsui et al., 1992), turnover (Jackson et al., 1991), job satisfaction (Wharton & Baron, 1987, 1991), and frequency of communication (Zenger & Lawrence, 1989), both social identity theory and the similarity-attraction paradigm suggest that additional processes and criteria related to the work unit itself may also be affected by demographic similarity. For one, maintaining one's social identity and viewing this identity positively are overarching goals of social identity theory (James & Khoo, 1991). Specifically, social identity theory notes that individuals tend to support and positively evaluate the groups that embody salient aspects of their social identities because it builds their self-esteem and maintains a positive self-identity. A work unit in which the individual is similar in terms of demographic characteristics may, therefore, increase the individual's identification with that work group. In turn, it is likely that identification with a work unit "enhances support and commitment to it" (Ashforth & Mael, 1989, p. 25). Research suggests that social identification with a group affects attitudes and behaviors that are generally associated with group formation such as cohesion, cooperation, altruism, and positive evaluations of the group (Turner, 1982,1984). Conversely, a work unit in which the individual is dissimilar to others in terms of demographic characteristics may result in a loss of self-identity (James & Khoo, 1991). That is, membership in a work group in which an individual is dissimilar to others does not facilitate continuity for that individual's self-identity. Thus, to the extent that self-identity is important to a person, the lack of continuity in self-identity due to employment in a work group may prevent the individual from positively evaluating that work group and feeling a great deal of support and commitment toward the group. In addition, the similarity-attraction paradigm suggests that similarity between individuals within a group leads to a high degree of interpersonal attraction among members (Byrne, 1971; Newcomb, 1956). This interpersonal attraction, in turn, is thought to be positively related to many group-related processes, such as cohesiveness, desire to maintain group affiliation, friendship ties, and communication (Lincoln & Miller, 1979). If an individual is dissimilar to other work group members, tittle attraction will exist, which, in turn, will negatively affect the individual's attitudes toward that group. Overall, on the basis of both social identity theory and the similarity-attraction paradigm, it is hypothesized that the individual's attitudes toward the work unit itself will

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be affected by the individual's level of demographic similarity. Specifically, theory suggests that demographic similarity will be related to at least three work-group-related criteria: individuals' commitment to the group, individuals' feelings of group cohesiveness, and individuals' evaluations of the group. Hypothesis 1: The greater the similarity between an individual and the composition of the work unit, for the three demographic characteristics of gender, race-ethnicity, and tenure, the more positive the individual's attitudes will be toward the work group, as indicated by higher levels of work group commitment, greater feelings of group cohesiveness, and higher evaluations of work group productivity.

Demographic Similarity and Advancement Opportunities In addition to criteria related to the work group itself, the literature suggests that demographic similarity may affect criteria directly related to the individual. One outcome that may be influenced by demographic similarity is an individual's perceptions of opportunities for advancement within an organization. Both social identity theory and the similarity-attraction paradigm imply that individuals tend to hire others like themselves. This may produce a certain uniformity in the types of individuals who hold various positions within the organization. Thus, work groups in which a majority of members are similar in terms of demographic characteristics may perpetuate a stereotype or prototype of the characteristics that are viewed as important for effective functioning within certain positions, the work group, and the organization (James & Khoo, 1991). As noted by James and Khoo (1991),' 'individuals have stereotypes (orprototypes) not only of social groups, but also occupations, positions, and members of a particular organization" (p. 183). These prototypic characteristics are often referred to as peripheral characteristics because they are not necessarily related to individual effectiveness, yet they are perceived as essential for achieving success within an organization (Cox & Nkomo, 1986; Ranter & Stein, 1979). Individuals who are demographically dissimilar to the other members of their work groups may perceive that they do not possess these peripheral characteristics that are pan of the successful prototype and thus, view their chances for advancement within the organization as low (Fernandez, 1974, 1981). In addition, individuals who are demographically dissimilar to the rest of their work group may be less socially integrated into the informal networks within a work group. As noted previously, individuals are more likely to choose interactions and develop social networks with people who possess similar characteristics. Research has indicated that informal social networks are typically im-

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portant for finding out about job openings and advancement opportunities within an organization (Braddock & McPartland, 1987). As such, employees who are demographically dissimilar to members of their work group may be less integrated into the informal networks within the group, and thus would be likely to perceive that fewer promotional opportunities exist within the organization. In summary, we hypothesize that individuals who are demographically similar to the rest of their work units will perceive more opportunity for advancement than individuals who are demographically different from the rest of their work units. Hypothesis 2: The greater the similarity between an individual and the composition of the work unit, for the three demographic characteristics of gender, race-ethnicity, and tenure, the higher the individual's perceptions will be of opportunities for advancement within the organization.

Method Sample Participants in this sample included 1,584 employees from a major insurance company located in the southeastern United States. The sample represented over 90% of the total employee population. Across the total sample, the race-ethnicity breakdown was as follows: 63.3% White, 33.7% African American, and 1.2% Hispanic, 0.6% Asian American, and 1.2% other. Because the Asian subsample consisted of only 10 individuals, the sample size for this category was not adequate for inclusion within this study. In addition, we considered "other" to be an uninterpretable category and did not include those individuals in the final sample. Thus, the usable sample size was reduced to 1,554 and consisted of White, African American, and Hispanic participants. Of the usable sample, 80% of the respondents were female. With respect to organizational tenure, the breakdown was as follows: (a) 13% with less than 1 year of service, (b) 34% with 1 to less than 5 years, (c) 21% with 5 to less than 10 years, and (d) 32% with 10 or more years of service. In terms of job level, 56% of the sample were in clerical positions, 33% were in staff positions, and 11% were in management positions. A further assessment of the sample indicated that of those employees in clerical positions 47% were White, 51% were African American, and 2% were Hispanic; of those employees in staff positions, 81% were White, 18% were African American, and less than 1% were Hispanic; and of those employees in management positions, 85% were White and 15% were African American. Also, of those employees in clerical positions, 90% were female; of those employees in staff positions, 70% were female, and of those employees in management positions, 55% were female. It should be noted that this study's sample in comparison with other samples in relational demography studies (e.g., Jackson et al., 1991; Tsui et al., 1992; Zenger & Lawrence, 1989) is unique in that it contains a higher percentage of both African American and Hispanic respondents. Therefore, this sample contains more racial—ethnic diversity than samples that have been previously

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used for relational demography research. In addition, this sample differs from samples in other studies in that it contains work groups that range from predominantly White to predominantly minority. Such a range of racial—ethnic composition in work groups allows for more complete testing of relational demography. This sample is also predominantly female, whereas other samples in relational demography research have been predominantly male (e.g., Jackson et al., 1991; Tsui et al., 1992; Zenger & Lawrence, 1989). Predominantly female organizations are prevalent in a number of industries such as health care, banking, textiles, and insurance (U.S. Equal Employment Opportunity Commission, 1995). Thus, both the racial-ethnic and gender differences among this sample and others used in previous research can potentially increase the generalizability of the relational demography research.

Data Collection All data used in this study were collected from survey respondents by means of questionnaires. Confidentiality of responses was maintained by minimum respondent identification, off-site data processing, and use of group means and frequency counts for organizational feedback purposes. The measures used in the present study were part of a more extensive organizational opinion survey. Within this study, it was important to identify complete work groups. Therefore, during the survey administration, respondents were provided with a list of formal work unit names and were instructed to identify to which group they belonged on the front of the survey. The work unit names that were used in this list were those commonly used by the organization so that respondents would easily recognize the group to which they belonged. Overall, there were 98 formally structured work groups within the organization.

Dependent Variables A sponsor organization working with the researchers specified the type of response scale used to anchor the survey items to ensure compatibility between the data from this study and an existing database. Thus, sponsor guidelines required that all survey responses were made on a 4-point Likert-type scale with anchors ranging from strongly disagree (1) to strongly agree (4). Scale scores were computed by averaging the items that corresponded to each scale. Work group cohesiveness. A 7-item scale was used to measure the employees' feelings of work group cohesiveness. Shaw (1981) measured work group cohesiveness by assessing the degree to which group members are attracted to each other, the general morale of the group, and the degree to which group members coordinated efforts. Based upon this research, the measure of work group cohesiveness included the following items: (a) "Most of the employees in my work group get along well with each other," (b) "Most of the employees in my work group respect each other," (c) "Most of the employees in my work group trust each other," (d) "Most of the employees in my work group do their fair share of the work," (e) "Most of the employees in my work group cooperate to get the job done,'' ( f ) "Most of the employees in my work group are willing to

share ideas and information," and (g) "In my work group, there is strong teamwork.'' Work group commitment. The measure of work group commitment was used to assess the relative strength of an individual's identification and involvement with their work group (Mowday, Steers, & Porter, 1979). As noted by Mowday et al. (1979), attitudinal commitment is a state in which the individual identifies with a particular group and its goals and wishes to maintain membership in order to facilitate these goals. Based upon this work, employees' commitment to their work group was assessed with three items: (a) "I feel a high level of loyalty to my work group," (b) "I would have little or no regrets about leaving my work group" (reverse scored), and (c) "If asked, I would be willing to make an extra effort to help my work group." Work group productivity. Work group productivity or performance can be defined along a number of dimensions, such as efficiency, innovation, and quality (Ancona & Caldwell, 1992). As such, a 4-item scale was used to assess employees' perceptions of their work group's productivity. The items included were as follows: (a) "Most of the time my work group cuts unnecessary costs whenever possible," (b) "Most of the time my work group tries new ways to improve productivity," (c) "Most of the time my work group produces high-quality work," and (d) "Most of the time my work group is run efficiently." Advancement. Adapted from previous research (e.g., Katzell, Evans, & Korman, 1974; Smith, Kendall, & Hulin, 1969), employees' perceptions of the opportunities for advancement were measured with a 4-item scale consisting of the following items: (a) "I have opportunities for advancement and promotion," (b) "If I perform my job well, I am more likely to be promoted," (c) "People promoted are generally the most qualified among potential candidates," and (d) "The policies and practices of this company ensure all employees—regardless of their gender, racial origin, or physical abilities—have an equal chance for advancement.''

Independent Variable Demographic similarity. The independent variable of interest in this study is demographic similarity. Some previous research has used a Euclidean distance (D-score) formula or a difference score approach to operationalize the similarity between an individual's demographic characteristics and the composition of the work group (e.g., Jackson et al., 1991; Zenger & Lawrence, 1989). One commonly used formula is the square root of the summed squared differences between an individual's (Si) value on a specific demographic variable and the value on the same variable for every other individual within the work group (Sj~), divided by the total number of respondents (n) in the group, that is, D = (1/n) S [(S, - S,)2]"2. Thus, based on the £>-score approach, the construct of demographic similarity is derived from the two components of (a) the individual's score on a specific demographic characteristic and (b) all other work group members' scores on the same demographic characteristic. Whereas the Z>-score has been used in some of the existing relational demography studies (e.g., Jackson et al., 1991), there are a number of inherent limitations with this type of formula for behavioral research (Edwards, 1994), and, in particular, for

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research on demographic diversity. For one, the use of difference scores, in general, contributes to the conceptual ambiguity of the demographic similarity construct. That is, the D score collapses two conceptually distinct component measures (i.e., a demographic characteristic and its analogous work group composition measure) into a single score, thereby confounding the effects of the component measures (Edwards, 1994). Thus, the D score ignores the possibility that the separate components of the measure, such as the individual's race-ethnicity or the raceethnic composition of the work group, may each contribute relevant information for predicting individual attitudes and behaviors. A second, related limitation in the use of D scores is that they do not account for differences in direction (Edwards, 1994). For example, in assessing similarity in race-ethnicity, a f) score may indicate that an individual is quite different in race-ethnicity from the rest of the work group. However, the D score does not indicate whether the individual is African American, White, or Hispanic. Because of the limitations with the D score, we followed the approach of several other relational demography studies and used an interaction term to operationalize demographic similarity within this study (Fagenson, 1990; Ferris et al., 1991; Flynn & Shore, 1994; Mellor, 1995). In general, the interaction term approach focuses on the individual demographic attribute relative to the group composition for the same attribute (Klein, Dansereau, & Hall, 1994). That is, the interaction term (viz., Individual Demographic Characteristic X Group Demographic Composition) measures the similarity between an individual's demographic characteristic (e.g., race-ethnicity) and the demographic composition of the work group (e.g., race-ethnic composition). It is expected that the interaction term will account for significant variance in work-related attitudes and behaviors beyond that accounted for by either of the two components independently (i.e., the individual demographic characteristic and the work group demographic composition; Ferris et al., 1991). In order to operationalize demographic similarity through the interaction term approach, the individual demographic characteristics and work group demographic composition variables were measured as follows. Individual demographics. The demographic characteristics of race-ethnicity, gender, and organizational tenure were measured in the following format: For the race-ethnicity variable, 1 = White (not of Hispanic origin); 2 = African American (not of Hispanic origin); and 3 = Hispanic. For gender, 1 = female and 2 = male. For organizational tenure, 1 = less than 1 year; 2 = 1 to less than 5 years; 3 = 5 to less than 10 years; and 4 = more than 10 years. Work group demographic composition variables. Three work group composition measures were calculated based on the demographic composition of each of the 98 work groups within the organization. For the race-ethnic composition variable, each work group was categorized as either of the following: 1 = mostly White, 2 = 50/50 White and minority, or 3 = mostly minority. If a work group was composed of more than 60% White, it was classified as mostly White; if a work group was between 40% and 60% White, it was classified as a 50/50 White and minority group; and if a work group was less than 40% White, it was classified as a minority group. From the 98 work

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groups, 65 groups were categorized as mostly White, 19 as 50/ 50 White and minority, and 14 as mostly minority, where the minority classification consisted of African American and Hispanic participants. It should be noted that none of the work groups were comprised of a majority of Hispanic participants. Therefore, rather than eliminating the Hispanic subgroup from the study, Hispanic and African American participants were both considered minorities only for the purpose of calculating the work group race-ethnic compositions. Tb verify that the race-ethnic classifications were accurate for each work group, we checked to see if the race-ethnic composition of the group would change by adding the respondents who were Asian or' 'other'' back into the sample as minorities. For all work groups, the race-ethnic classification (i.e., mostly minority, 50/50 White and minority, or mostly White) remained the same even with the addition of the Asian and "other" respondents. This was probably due to the small number of respondents who were in these eliminated categories and the fact that none of the eliminated respondents belonged to the same work group. For the group gender composition variable, each work group was categorized as either of the following: 1 = mostly female, 2 = 50/50 female and male, or 3 = mostly male. If a work group was composed of more than 60% women, it was classified as mostly female; if a work group was between 40% and 60% female, it was classified as a 50/50 female and male group; if a work group was less than 40% female, it was classified as a mostly male group. From the 98 work groups, 75 were categorized as mostly female, 12 as 50/50 female and male, 11 as mostly male. For the group tenure composition variable, each work group was categorized as either of the following: 1 = mostly junior, 2 = 50/50 senior and junior, or 3 = mostly senior, where senior designated 5 or more years of service and junior designated less than 5 years of service. If a work group was composed of more than 60% juniors, it was classified as mostly junior; if a work group was between 40% and 60% juniors, it was classified as a 50/50 senior and junior group; if a work group was less than 40% junior, it was classified as a mostly senior group. From the 98 work groups, 20 groups were categorized as mostly junior, 27 as 50/50 senior and junior, and 52 as mostly senior.

Control Variables Because the objective of the present study was to test the effects of demographic similarity on the dependent variables, it was necessary to control for additional variables that may cause spurious correlations between the predictor variables and the outcome variables. For example, many women and minorities are typically in lower level positions (Cox & Nkomo, 1990; Dipboye, 1987) and employee attitudes may be influenced by the job level held by these employees. Thus, the job level of the individual was controlled to determine whether the individual and group demographic variables affected the work-related attitudes after job level was accounted for. Job level was measured on a 5-point progressive level scale with 1 designating nonexempt employees (Grade Level 14-24) and 5 designating senior vice-president. In addition, previous research has indicated that group size may affect individuals' attitudes (Shaw, 1981). For

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example, a meta-analysis on group size indicated that as work groups grew, members were more likely to be dissatisfied (Mullen, Symons, Hu, & Solas, 1989). Research has also found that as group size increases, group cohesiveness decreases (Thomas & Fink, 1963). Therefore, group size, as measured by the number of employees in a work group, was also included as a control variable. Within this study, the size of the work groups ranged from 4 to 30 (Man = 17; M = 17.97).

four-factor measurement model among the dependent variables of group cohesiveness, group productivity, group commitment, and advancement opportunities. Whereas the chi-square was statistically significant, x 2 (129, N = 1050) = 964.87, p < .05, the CFI, TLI, and GFI were around .90 (CFI = .91, TLI = .89, GFI = .90), and the RMSEA was .08, supporting the acceptability of the fit. Further, the four-factor model better fit the data than the one-factor model. All of the parameter estimates (factor loadings) for the four-factor model were also significant at p < .05 and ranged from .30 to .89. Another test of the discriminant validity, based on calculating the confidence intervals (two standard errors) around the correlations, found that none of the confidence intervals contained the value of 1.0, adding further support for the four-factor model (Anderson & Gerbing, 1988). The means, standard deviations, correlations, and reliabilities for the four measures of group cohesiveness, group productivity, group commitment, and advancement opportunities are presented in Table 2.

Results Confirmatory Factor Analyses Confirmatory factor analyses (CFAs) with LISREL 8 (Joreskog & Sorbom, 1993) were conducted to assess the structure of the dependent measures (group cohesiveness, group productivity, group commitment, and advancement opportunities). Several statistics were used to evaluate the overall model fit for the CFAs. Specifically, the following indexes were used to evaluate model fit: (a) the chi-square statistic, (b) the Comparative Fit Index (CFI; Bentler, 1990), (c) the Tucker-Lewis index (TLI; Tucker & Lewis, 1973), (d) the goodness-of-fit index (GFI), and (e) the root mean square error of approximation (RMSEA; Steiger, 1990). Whereas there are no specific guidelines for assessing the fit of a measurement model, in general, the larger the values of the TLI, GFI, and CFI (i.e., values .90 or above), the better the fit of the model (Bollen, 1989). Also, the RMSEA value should ideally be .05, which indicates a close fit, but values up to .08 represent reasonable errors of approximation (Browne & Cudek, 1993). A nonsignificant chi-square is also an indication of acceptable fit. To assess the discriminability of the fourfactor model, we examined whether a single-factor model provided a better fit to the data than the four-factor model. As such, we compared the models by evaluating the difference in cm-squares between the models (Widamen, 1985 ). A nonsignificant chi-square difference value indicates acceptance of the most parsimonious model being compared (i.e., the one-factor model). Alternatively, a significant chi-square difference value indicates acceptance of the less constrained model (i.e., the four-factor model). As depicted in Table 1, the CFA results supported a

Tests of Hypotheses 1 and 2 Because of the unequal sample sizes of the various demographic groups, the regression approach for analysis of covariance (ANCOVA) was used to test the hypotheses (Neter, Wasserman, & Kutner, 1989). A hierarchical procedure was used to assess whether a block of independent variables made a unique contribution to the dependent variables (Cohen & Cohen, 1983). If the inclusion of a block of variables significantly increased the amount of variance explained for a dependent variable, then that block of independent variables was considered to be important. For each hypothesis, the following hierarchical steps were followed: (a) In the first step of the analysis, we entered job level and group size as a block (Step 1); (b) in the second step of the hierarchical analysis, the simple demographic variables, as well as the work group composition variables, were entered as a block (Step 2); (c) and finally, in the third step of the analysis, the interactions between the simple demographic variables and the work group composition variables were added as a block (Step 3).

Table 1 Fit Indices for Confirmatory Factor Analyses Model 1 . Four-factor model 2. Single-factor model 3. Null model

964.87*** 2,995.87*** 9,232.09***

df

CFI

TLI

GFI

RMSEA

129 135

.91 .68

.89 .64

.90 .72

.08 .14

A*2

2,031.00***

6

153

Note. CFI = comparative fit index; TLI = Tucker-Lewis Index; GFI = root mean square error of approximation. ***;>< .001.

goodness-of-fit index; RMSEA =

349

RELATIONAL DEMOGRAPHY AND EMPLOYEE ATTITUDES

Table 2

Means, Standard Deviations, Correlations, and Reliabilities for the Dependent Variables

SD

Dependent variable \ . Work group productivity 2. Work group cohesiveness 3. Work group commitment 4. Advancement opportunities

2.82 2.87 3.14 2.28

.59 .63 .55 .75

(.75)

.60 .65 .42

(.92)

.62 .31

(.69)

.28

(.82)

Note. All correlations are significant at p < .001. The composite reliabilities are on the diagonal in parentheses.

In Steps 1 and 2, the hierarchical procedure assessed the proportion of variance in the dependent variable explained by the control variables and the main effects, respectively. In Step 3, a significant increase in R2 explained over the main effects by the set of interaction terms indicated that the block of Individual Demographics X Group Composition interactions significantly influenced the dependent variable. The results of the final step were of major interest in this study because they provided evidence of the significance of demographic similarity as operationalized by the Individual Demographics x Group Composition interactions. The hierarchical blocking of variables allowed for the precise assessment of the amount of variance accounted for by the block of interaction terms and thus for a precise estimation of the effects of demographic similarity. Overall, if the results from the hierarchical procedure indicated that the block of interaction terms significantly influenced a dependent variable, post hoc tests for each of the individual interaction terms were conducted. That is, if the change in K2 (A/? 2 ) for the block of interaction terms was significant, the Fs associated with each of the interaction terms were assessed for significance. If the overall F was significant for an interaction term, then pairwise t tests were conducted to compare the means of the groups represented by the interaction term. Following these procedures provided "stringent control" over the inflation of the Type I error rate associated with the tests of the hypotheses (Cohen & Cohen, 1983; pp. 172-176). Hypothesis 1. Hypothesis 1 predicted that the greater the similarity between an individual's demographic characteristics and others in a work group, the more positive would be the individual's attitudes toward the work group, as indicated by higher perceptions of work group productivity, higher levels of work group commitment, and greater feelings of group cohesiveness. As depicted in Table 3, the results indicated that there was a significant increase in R 2 over the main effects by the block of interactions for the dependent variables of work group productivity (AR 2 = .02, p < .01) and work group commitment (A/?2 = .02, p < .01). Whereas the results for both work group productivity and commitment were significant, the block of similarity

interaction terms did not significantly increase the prediction of work group cohesiveness (AR2 = .01, p > .05). Therefore, it was concluded that an individual's demographic similarity to his or her work group (as measured by the interaction terms) affected the individual's perceptions of group productivity and commitment to the work group, but not the individual's feelings of work group cohesiveness. Because the overall blocks of similarity interactions for work group productivity and work group commitment were significant, each individual interaction (i.e., Gender X Gender Composition, Race-Ethnicity X Race-Ethnic Composition, Tenure X Tenure Composition) was tested for significance (Cohen & Cohen, 1983). Only the RaceEdinicity X Race-Ethnic Composition interaction term was significant for work group productivity, and work group commitment. The cell means created by the interaction of Race-Ethnicity X Race-Ethnic composition for the dependent variables of work group productivity and work group commitment are presented in Table 4. In addition, Figure 1 shows the nature of these interaction effects for both of the dependent variables. The results from the pairwise t tests indicated that White participants, overall, exhibited significantly lower levels of work group commitment and perceptions of work group productivity when they were in work groups composed of mostly minorities than when they were in work groups composed of mostly White participants or work groups composed of 50% White participants and 50% minority participants. There were no significant differences between White participants in mostly White work groups and white participants in 50/50 work groups for both work group productivity and work group commitment. Overall, there appeared to be a threshold effect for race-ethnic similarity where White participants exhibited significantly lower attitudes toward their work group only when they became the minority (i.e., less than 40% White participants in the work group). African American participants had relatively the same perceptions of work group productivity across all three types of work groups (e.g., mostly White, 50/50, and mostly minority work groups). Thus, race-ethnic similarity did not effect African American participants' evalu-

350

RIORDAN AND SHORE

Table 3 Results From Analyses of Covariance Work group productivity Step

A.R2'

Step 1 Job level Group size Step 2 Race-Ethnicity Gender Tenure Race -Ethnic composition Gender composition Tenure composition Step 3 Race-Ethnicity X Race-Ethnic Composition Gender X Gender Composition Tenure X Tenure Composition Overall model F Total fl2 Adjusted fi2

.04**

Work group commitment Atf 2 "

F"

Work group cohesiveness

F"

.07** 22.81*** 21.78***

.02**

.03***

1.39 0.34 4.19** 13.28*** 0.42 1.63

.03** 27.11*** 0.92

.02***

.15***

0.00 0.53 4.93** 0.84 1.84 0.80

23.63*** 3.26 39.55*** 7.69 0.62 0.87

.01

.02*** 4 79*** 0.17 0.46

.02***

5.86*** 0.45 0.62 7.53*** .11 .10

F"

9.50** 3.12

1.89 5.46* 6.06**» 6.68** 0.93 0.54

.02***

AS2'

F"

61.77*** 3.23

.03***

5.88*** .09 .07

AK 2 "

Advancement opportunities

2.73* 0.01 0.58

4.44** 0.46 0.93

3.12** .05 .03

13.52*** .19 .17

* These statistics represent the incremental variance accounted for in the dependent variables when a block (step) of variables is added to each model. * These statistics represent the F ratios for the control and independent variables within the model. * p < . 0 5 . * * p < . 0 1 . ***p